4/25/20241 min read

The sharing economy concept, which involves lending idle goods or services to those in need to optimize resource use, has become a focal point in today's consumer culture and economic systems, thanks to more rational consumption patterns and advances in information technology.

However, as the sharing economy expands rapidly and user numbers increase, several negative effects have surfaced, including declining service quality, early market entrants dominating, strong opposition from existing industry workers, and regulatory challenges.

Blockchain technology facilitates the digitization of a broader range of assets, enhancing scale economies, proving crucial for developing the sharing economy. For example, IO.NET has pioneered the utilization of idle computing resources, demonstrating potential in this area.

With industries' increasing demand for diversity and system design complexity, optimizing systems has become critical. The limited resources and the asymmetrical development among various service systems exacerbate these challenges. The sharing economy, which lends idle goods or services, offers vital insights into solving these optimization issues.

The growth of AI technology has spiked demand for high-performance computing resources like GPUs. Although AI could transform and improve our lives in many ways, the lack of cost-effective, scalable computing resources hinders many AI startups from expanding their projects' scope and capabilities. The high costs and long wait times for popular computing chips, coupled with limited rental options, could stifle innovation within the AI industry and cause significant social impacts due to market asymmetry.

Ultimately, the key issue is ensuring an adequate supply of computing resources that are both cost-effective and high-quality. IO.NET, based on the Solana platform, addresses this by integrating idle computing resources from data centers, miners, and consumers with projects like Render Network and Filecoin. Providers earn tokens as rewards, while users employ these tokens economically to configure their GPU clusters with various types of idle computing resources.

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